Testing for neutrality in samples with sequencing errors.

Abstract:

:Many data sets one could use for population genetics contain artifactual sites, i.e., sequencing errors. Here, we first explore the impact of such errors on several common summary statistics, assuming that sequencing errors are mostly singletons. We thus show that in the presence of those errors, estimators of can be strongly biased. We further show that even with a moderate number of sequencing errors, neutrality tests based on the frequency spectrum reject neutrality. This implies that analyses of data sets with such errors will systematically lead to wrong inferences of evolutionary scenarios. To avoid to these errors, we propose two new estimators of theta that ignore singletons as well as two new tests Y and Y* that can be used to test neutrality despite sequencing errors. All in all, we show that even though singletons are ignored, these new tests show some power to detect deviations from a standard neutral model. We therefore advise the use of these new tests to strengthen conclusions in suspicious data sets.

journal_name

Genetics

journal_title

Genetics

authors

Achaz G

doi

10.1534/genetics.107.082198

subject

Has Abstract

pub_date

2008-07-01 00:00:00

pages

1409-24

issue

3

eissn

0016-6731

issn

1943-2631

pii

genetics.107.082198

journal_volume

179

pub_type

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